• Who's used R?
• Who's used RMarkdown?

This talk isn't about coding.

It's about improving what we do.

The Excel-Word approach is looooong and error-prone. Exaggerated example:

1. Receive non-machine-readable data in Excel format
2. Use a pre-prepared Excel template to reformat the data
3. Generate figures, tables and plots
4. Copy and paste to ~100-page Word document
5. Find error/need to alter something
6. Fix it
7. Spend ages re-copy-pasting the updated bits
8. Get confused about the current working version
9. Repeat steps 5 to 7 until 4am

Questions to ask yourself:

• are the steps recorded?
• what's the chance of human error (e.g. bad copy-paste)?
• is it easy to keep track of changes?
• could someone else reproduce it from scratch independently?

We can reduce error and go faster with R Markdown.

1. Receive machine-readable data in Excel format
2. Run a pre-prepared file written with R Markdown
3. Make minor tweaks if needed and re-render stress-free
4. Use the saved time to prepare more informative commentary and have a cup of tea

A document with filetype .Rmd in which you:

• write plain text that's 'marked-up' with symbols (*, [], ^, etc)
• embed R code to read, process and visualise data
• click a button to render it to a HTML, Word or PDF

This is already being done in the department and across government (Reproducible Analytical Pipelines).

Enclosed in three hyphens. Specify metadata and what output should be produced.

---
title: "Your title"
author: "Your name"
date: "The date"
output:
  word_document:
    reference_docx: mystyles.docx
    highlight: "tango"
---

You type:

*Italic*, **bold** super^script^ and a [link](www.gov.uk).

You get:

Italic, bold, super^script and a link.

You can write some R code in the middle of a sentence!

Wrap the code in backticks (the button under the Esc key) and start it with the letter r.

You type:

The answer to 1 + 1 is `r 1 + 1`

You get:

The answer to 1 + 1 is 2

Let's say my_value <- "Lotad"

You type:

The best Pokemon is `r my_value`

You get:

The best Pokemon is Lotad

You type:

Here's an important plot of chick weights and feed types.

```{r chicks}
chickwts %>%
  group_by(feed) %>% 
  ggplot() +
  geom_col(aes(x = feed, y = weight))
```

You get:

Here's an important table of chick weights and feed types.

1. In RStudio: File > New File > R Markdown
2. Write your text and embed your code
3. Click 'Knit' to render the document
4. The file is output to your current working directory

DEMO TIME!

Your R Markdown is rendered into 'plain' markdown by the package knitr (hence why you 'knit' to render the document), then something called pandoc converts it from markdown to your output format.

.Rmd ➡️ knitr ➡️ .md ➡️ pandoc ➡️ .html/.pdf/.docx

This isn't essential knowledge.

• In RStudio: Help > Cheatsheets for hints and tips.
• Introduction to R Markdown (webpages featuring video)
• Getting started with R Markdown (video, 1 hr)
• See the R Markdown gallery for examples of other document types, including dashboards, interactive documents, presentations (like this one) and books with R Markdown
• 'Knitting club', a Coffee & Coding session (webpage)
• A workflow with R Markdown works much better using an R Project and version control, which are subjects for another day